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Muhammad Zidni Subarkah
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Analisis Klaster K-Means Dan Visualisasi Data Spasial Berdasarkan Karakteristik Persebaran Covid-19 Dan Pelanggaran Protokol Kesehatan Di Jawa Tengah Rosi Anisya Faujia; Muhammad Zidni Subarkah
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.52 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1222

Abstract

The world is currently faced with the Covid-19 virus pandemic with a significant spike in the spread of cases, especially in Indonesia. The high intensity of the spread of the virus is influenced by the violation of health protocols. In this analysis, the authors took a sample of areas in Central Java using the K-Means Clustering and GeoDa spatial analyze methods with the aim of knowing the characteristics of the spread of Covid-19 in Central Java with indications of health protocol violations. The best number of clusters was obtained, namely 4 clusters with a 74% confidence level. Cluster 1 has the highest confirmed cases of Covid-19. Cluster 2 has the highest health protocol violations. Cluster 3 has the lowest confirmed cases of Covid-19. Cluster 4 had the lowest health protocol violations. The author hopes that this analysis can be a reference for the government to reduce positive number of Covid-19.
Analisis Sentimen Review Tempat Wisata Pada Data Online Travel Agency Di Yogyakarta Menggunakan Model Neural Network IndoBERTweet Fine Tuning Muhammad Zidni Subarkah; Martina Hilda; Etik Zukhronah
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (513.868 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1246

Abstract

Tourism is a leading sector in Indonesia, one of which is D.I. Yogyakarta. In 2017, the total number of tourists visiting DIY was 5,229,298. The high intensity of tourist visits is directly proportional to data on people's preferences for tourist attractions. From this problem, authors are interested in conducting a sentiment analysis of tourist attractions with the IndoBERTweet Fine Tuning Neural Network model using Online Travel Agency (OTA) data. This analysis is intended so that the government and local tourism managers can easily take a decision or policy in increasing the comfort of tourist attractions. Based on this analysis, five tourist attractions with the highest number of visitor reviews were obtained, namely, Malioboro Street, Tamansari Water Palace, Yogyakarta Palace, Yogyakarta Smart Park, and Yogyakarta Monument. Sentiment analysis of this classification produces an accuracy value of 92.84%, with weighted average recall of 93%, precision of 92%, and F1-Score of 93%.
Analisis Sentimen Pelaksanaan Vaksinasi Covid-19 secara Massal pada Media Sosial Twitter Adinda Febby Nuraini; Rosma Dian Pertiwi; Muhammad Zidni Subarkah; Kiki Ferawati
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.085 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1564

Abstract

The corona virus or Covid-19 attacks almost all countries in the world, as well as Indonesia. The Indonesian government has implemented several policies to deal with the spread of the Covid-19 in the community, namely by mass vaccination. The implementation of mass vaccination has become trending on Twitter. This study aims to analyze the sentiment of mass vaccination in Indonesia using a comparison between Naïve Bayes, Random Forest, and Support Vector Machine (SVM) methods. The results showed that SVM classification method has F1-Score Weighted Average higher than other methods, which was 84%. In addition, it can be concluded that most of the community is pro against the implementation of mass vaccines. So, SVM method can be used by the government to classify public sentiment towards the next mass vaccination and basis for the government to maintain this mass vaccination program as an effort to prevent the spread of Covid-19.
Co-Authors Adinda Febby Nuraini Kiki Ferawati Martina Hilda Rosi Anisya Faujia Rosma Dian Pertiwi Zukhronah, Etik